Last Update Date: Jun 15, 2020
- Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) images
E Acar et al, MEDRXIV, June 14, 2020 - Social media as a tool for scientific updating at the time of COVID pandemic
R Murri et al, MEDRXIV, June 14, 2020 - A Machine Learning Solution Framework for Combatting COVID-19 in Smart Cities from Multiple Dimensions
I Abaker et al, MEDRXIV, June 14, 2020 - How Data Became One of the Most Powerful tools to fight an epidemic
S Johnson, New York Magazine, June 2020 - Machine Learning Maps Research Needs in COVID-19 Literature
AL Doanvo et al, BIORXIV, June 12, 2020 - An imperfect tool: COVID-19 'test & trace' success relies on minimising the impact of false negatives and continuation of physical distancing.
EL Davis et al, MEDRXIV, June 13, 2020 - Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States
WE Allen et al, MEDRXIV, June 11, 2020 - Using Digital Data to Protect and Promote the Most Vulnerable in the Fight Against COVID-19
R Chunara et al, Frot Public Health, June 12, 2020 - Artificial-intelligence tools aim to tame the coronavirus literature
M Hutson, Nature, June 11, 2020 - Sex differences in immune responses to SARS-CoV-2 that underlie disease outcomes
T Takahashi et al, MEDRXIV, June 9, 2020 - Lots of us are infected by the coronavirus — and don’t know it. Here’s what that means.
DP Oran et al, Washington Post, June 11, 2020 - Factors affecting COVID-19 outcomes in cancer patients − A first report from Guys Cancer Centre in London
B Russel et al, MEDRXIV, June 9, 2020 - Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group
V Sounderajah et al, Nature Medicine, June 9, 2020 - How Social Media and 3D Printing Tackles the PPE Shortage during Covid - 19 Pandemic
N Vordos et al, MEDRXIV, June 8, 2020 - Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.
Dovgan Erik et al. PloS one 2020 15(6) e0233976 - A machine learning approach predicts future risk to suicidal ideation from social media data.
Roy Arunima et al. NPJ digital medicine 2020 378 - Deep Learning Approaches Towards Skin Lesion Segmentation and Classification from Dermoscopic Images - A Review.
Baig Ramsha et al. Current medical imaging 2020 16(5) 513-533 - Wearable sensor-based evaluation of psychosocial stress in patients with metabolic syndrome.
Patlar Akbulut Fatma et al. Artificial intelligence in medicine 2020 Apr 104101824 - Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing.
Hosseini Mohammad-Parsa et al. Artificial intelligence in medicine 2020 Apr 104101813 - Early detection of sepsis utilizing deep learning on electronic health record event sequences.
Lauritsen Simon Meyer et al. Artificial intelligence in medicine 2020 Apr 104101820
Disclaimer: Articles listed in Non-Genomics Precision Health Update are selected by the CDC Office of Public Health Genomics to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
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